Description

Lead the architecture and delivery of production-grade AI/ML solutions across cloud and edge environments.

Responsibilities

• Design and implement cloud-native data architectures using Microsoft Azure, AWS, or GCP.
• Manage the end-to-end AI/ML model lifecycle using MLOps practices, including explainability and bias mitigation.
• Integrate data pipelines across SAP platforms (S/4HANA, BW, Datasphere), Microsoft Dynamics, and PLM systems.
• Embed privacy, security, and compliance controls such as encryption and access governance into all data and AI solutions.
• Build and deploy Generative AI frameworks, Copilot integrations, and automated business use cases.

Required Skills

• 10–15 years of experience in data architecture, machine learning engineering, and AI platform development.
• Hands-on expertise with Databricks, Snowflake, MLflow, Kubernetes, TensorFlow, and PyTorch.
• Proficiency with Microsoft Fabric ecosystem, including Data Factory, OneLake, and Power BI.
• Experience in regulated industries (MedTech, Pharma, or Healthcare) with knowledge of ISO 13485, FDA 21 CFR Part 11, HIPAA, or GDPR.
• Experience handling PHI/PII securely within data architectures.
• Technical proficiency with SAP S/4HANA and Datasphere.
• Bachelor's degree in Computer Science, Information Systems, Engineering, or a related technical field.
• Ability to travel up to 20% domestically and internationally.

Preferred Skills

• Advanced degree or certifications in AI, Machine Learning, Data Engineering, or Cloud Architecture.
• Relevant certifications such as Azure Solutions Architect Expert, AWS Certified Solutions Architect – Professional, or Databricks Certified Data Engineer Professional.

Key Skills

Education

Bachelor's degree